Liu Li, Mu Ben-Rong, Zhou Ya, Wu Qing-Lin, Li Bin, Wang Dong-Mei, Lu Mei-Hong
Chongqing Key Laboratory of Sichuan-Chongqing Co-Construction for Diagnosis and Treatment of Infectious Diseases Integrated Traditional Chinese and Western Medicine, College of Medical Technology, Chengdu University of Traditional Chinese Medicine, 1166 Liutai Avenue, Wenjiang District, Chengdu, 611137, Sichuan, China.
Department of Respiratory Medicine, Guangyuan Hospital of Traditional Chinese Medicine, No.133 Jianshe Road, Lizhou District, Guangyuan, 628099, Sichuan, China.
Mol Biotechnol. 2025 Jan 22. doi: 10.1007/s12033-024-01356-7.
Quantitative polymerase chain reaction (qPCR) is a vital molecular technique for biomarker detection; however, its clinical application is impeded by the scarcity of robust biomarkers and the inherent limitations of the technology. This study conducted a bibliometric analysis of 4063 qPCR-based biomarker studies sourced from the Web of Science (WOS) database, employing VOSviewer and CiteSpace to generate multi-dimensional structural insights into this field. The results reveal a growing trend in research within this domain, with gene expression analysis playing a central role in the identification of potential biomarkers. Among these, cancer-related biomarkers are the most prominent, while research on biomarkers for other diseases remains limited. Liquid biopsy biomarkers, including microRNA (miRNA), circulating free DNA (cfDNA), and circulating tumor DNA (ctDNA), are increasingly being explored. The integration of bioinformatics, omics analysis, and high-throughput technologies with qPCR is accelerating biomarker discovery. Furthermore, large-scale parallel sequencing is emerging as a potential alternative to relative quantification and microarray techniques. Nevertheless, qPCR remains essential for validating specific biomarkers, and further standardization of its protocols is necessary to enhance reliability. This study provides a systematic analysis of qPCR-based biomarker research and underscores the need for future technological integration and standardization to facilitate broader clinical applications.
定量聚合酶链反应（qPCR）是一种用于生物标志物检测的重要分子技术；然而，其临床应用受到可靠生物标志物稀缺以及该技术固有局限性的阻碍。本研究对来自科学网（WOS）数据库的4063项基于qPCR的生物标志物研究进行了文献计量分析，采用VOSviewer和CiteSpace对该领域生成多维度结构洞察。结果显示该领域的研究呈增长趋势，基因表达分析在潜在生物标志物的识别中发挥核心作用。其中，癌症相关生物标志物最为突出，而针对其他疾病的生物标志物研究仍然有限。包括微小RNA（miRNA）、循环游离DNA（cfDNA）和循环肿瘤DNA（ctDNA）在内的液体活检生物标志物正得到越来越多的探索。生物信息学、组学分析和高通量技术与qPCR的整合正在加速生物标志物的发现。此外，大规模平行测序正成为相对定量和微阵列技术的一种潜在替代方法。尽管如此，qPCR对于验证特定生物标志物仍然至关重要，并且有必要进一步规范其方案以提高可靠性。本研究对基于qPCR的生物标志物研究进行了系统分析，并强调了未来技术整合和标准化以促进更广泛临床应用的必要性。
